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acs.html
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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="google-site-verification" content="G4gClB66Jr2h0XiecdD1OyTE0HCHwwS707_GIuEMCfU" />
<meta name="description"
content="The DRISHTI-ROBOCON is a student initiative at SVNIT to build robots for participating in ABU-ROBOCON">
<meta name="keywords" content="Drishti,ROBOCON, robocon,WE,ME">
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
<title>
ACS
</title>
<link rel="apple-touch-icon" sizes="180x180" href="favicon_io/apple-touch-icon.png">
<link rel="icon" type="image/png" sizes="32x32" href="favicon_io/favicon-32x32.png">
<link rel="icon" type="image/png" sizes="16x16" href="favicon_io/favicon-16x16.png">
<link rel="manifest" href="favicon_io/site.webmanifest">
<link href="css/all.min.css" rel="stylesheet">
<link href="css/fontawesome.min.css" rel="stylesheet">
<link rel="stylesheet" href="css/bootstrap.min.css">
<link rel="stylesheet" type="text/css" media="screen" href="footer.css">
<link rel="stylesheet" type="text/css" media="screen" href="acs.css">
</head>
<body>
<div class="main-div">
<nav class="navbar navbar-expand-md navbar-light" style="background-color: rgba(2,2,2,0.4);">
<a href="http://svnit.ac.in/" class="navbar-brand">
<img class="nit_photo" src="images/svnit.png">
</a>
<div class="navbar-brand v1"></div>
<a href="https://drishti-svnit.github.io/drishti/" class="navbar-brand">
<img src="images/logoleft.jpg" class="svnit_photo">
</a>
<button type="button" class="navbar-toggler" data-toggle="collapse" data-target="#menu">
<span class="navbar-toggler-icon"></span>
</button>
<div class="collapse navbar-collapse" id="menu">
<ul class="navbar-nav ml-auto">
<li class="nav-item" style="font-weight: bold; margin-right: 20px;"><a href="index.html"
class="nav-link">Home</a></li>
<li class="nav-item" style="font-weight: bold; margin-right: 20px;"><a href="gallery.html"
class="nav-link">Gallery</a></li>
<li class="nav-item dropdown " style="font-weight: bold; margin-right: 20px;">
<a href="#" class="nav-link dropdown-toogle" data-toggle="dropdown">Projects</a>
<div class="dropdown-menu" style="background-color: rgb(220,220,220);">
<a href="tunex.html" class="dropdown-item">
Tunex
</a>
<a href="virtuon.html" class="dropdown-item">
Virtuon
</a>
<a href="gisa.html" class="dropdown-item">
GISA
</a>
<a href="planet.html" class="dropdown-item">
PlaNet
</a>
<a href="acs.html" class="dropdown-item">
Automated-Check-in-System
</a>
<a href="aicolorization.html" class="dropdown-item">
Ai-image-Colorization
</a>
</div>
</li>
<li class="nav-item" style="font-weight: bold; margin-right: 40px;"><a href="#down"
class="nav-link">Contact</a></li>
</ul>
</div>
</nav>
<div class="ref-image">
<div class="ref-title">
<h1>
Automated-Check-in-System
</h1>
<h3>2018-2019</h3>
</div>
</div>
</div>
<br><br><br>
<div class="ref-aim">
<h1>THOUGHT</h1>
<p> The main aim of the project is to build a Face Recognition System. This project detects the face of a
person in real time from stored database.Face Detection is the first step for Face Recognition which is
followed by extracting features in form of embeddings from the input image. Test image is passed into the
program and its features are calculated and these embeddings are compared with embeddings of our database
and the person is recognized.</p>
<p><b>MODEL</b></p>
<P>
Model for face recognition was trained for the following techniques:
<ul>
<li>FaceNet</li>
<li>Eigen Values</li>
<li>Local Binary Pattern Histograms(LBPH)</li>
<li>Convolutional Neural Networks(CNNs)</li>
</ul>
</P>
<div class="image">
<img src="images/facenet.jpeg">
</div>
<p><b>WORKFLOW</b></p>
<P>
We developed a real time dataset by capturing a short video clip of the people precisely to
be of 7-8 seconds. We further segmented it to fetch the frames by using a python code. It
approximately resulted in 140-150 frames per person.
Model is trained according to the above Flow charts.
</P>
<div class="image">
<img src="images/ACS/FLOWCHART3.png">
</div>
<p><b>RESULT</b></p>
<P>
We reached to an accuracy of about 84.67% while working in real time with the model. We have been continuously analyzing the approach and making efforts to increase the accuracy of the system.
</P>
<div class="image">
<img src="images/ACS/result.jpeg">
</div>
</div>
</body>
<script src="js/jquery.min.js"></script>
<script src="js/bootstrap.min.js"></script>
</html>